{"id":"W3124723151","doi":"10.2308/accr.2002.77.1.1","title":"“Cost of Capital” in Residual Income for Performance Evaluation","year":2002,"lang":"en","type":"article","venue":"The Accounting Review","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":259,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Diversification (marketing strategy); Actuarial science; Offset (computer science); Investment decisions; Investment (military); Microeconomics; Cost of capital; Capital budgeting; Economics; Finance; Incentive; Marketing; Behavioral economics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008396581,0.001682108,0.001013594,0.001683514,0.0008696673,0.005024927,0.001689772,0.003061325,0.006818411],"category_scores_gemma":[0.03516861,0.0003986649,0.0008230958,0.001734715,0.002903791,0.006842348,0.00259391,0.002544669,0.0007499176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004043107,"about_ca_system_score_gemma":0.001546411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002839749,"about_ca_topic_score_gemma":0.002902694,"domain_scores_codex":[0.9922976,0.004471432,0.0002679091,0.0005679624,0.001721631,0.0006735323],"domain_scores_gemma":[0.9855286,0.01034082,0.001256913,0.001338411,0.001159724,0.000375529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002129854,0.0001736907,0.005154881,0.0001682266,0.00004672198,0.0002898993,0.0001891039,0.1082022,0.0007749355,0.7925607,0.004904857,0.08732202],"study_design_scores_gemma":[0.00007014984,0.0005085681,0.006579365,0.0003614205,0.0001107807,0.0003662614,0.0002840747,0.3378365,0.002176435,0.6300089,0.02155727,0.000140237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.127186,0.008628637,0.6432922,0.01912812,0.0007144903,0.0005935213,0.0005377135,0.0005215497,0.1993977],"genre_scores_gemma":[0.939428,0.0009098137,0.05243047,0.0004258613,0.0003401505,0.0001993719,0.00009159776,0.00007098258,0.006103819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008396581,"threshold_uncertainty_score":0.04440588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04391449284615365,"score_gpt":0.2728909887496139,"score_spread":0.2289764959034602,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}